恒虚警率
计算机科学
稳健性(进化)
对比度(视觉)
假警报
像素
人工智能
帧速率
对比度
假阳性率
计算机视觉
度量(数据仓库)
模式识别(心理学)
算法
数学
操作系统
基因
化学
数据库
生物化学
作者
Jinhui Han,Yin Yu,Kun Liang,Honghui Zhang
标识
DOI:10.1117/1.oe.57.10.103105
摘要
It is always a challenging task to detect an infrared (IR) small target with high-detection rate, low false alarm rate, and high detection speed since the target usually has a small size and dim gray value, and the background is usually complex. Local contrast, which is based on the human visual system, has been proved efficient for IR small target detection, but existing local contrast algorithms are either difference-form or ratio-form and cannot enhance true target and suppress background simultaneously. In addition, most of them are pixel-level algorithms and require a huge amount of calculations. A simple but efficient method named subblock-level ratio-difference joint local contrast measure (SRDLCM) is proposed; it can enhance real small target and suppress complex background simultaneously. In addition, SRDLCM is calculated for each subblock but not each pixel, so its calculation amount can be reduced significantly. The experimental results on seven real IR sequences and one single-frame image dataset show that the proposed algorithm can achieve a good detection performance in detection rate and false alarm rate with a good robustness, and the time consumed for a single frame is only less than 0.04 s.
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